Edge CV Engineer — Production-Ready Vision for Food Waste

Mill; San Bruno (CA); On-site; USD 220,000 - 250,000; Full time

Job summary

Mill is seeking a Computer Vision Engineer to advance the CV technology behind Mill Commercial, turning food waste streams into actionable intelligence for large kitchen operators.

You will own modeling, training infra, and cloud-side evaluation harnesses, while guiding data-groundtruth workflows and model deployment decisions. This IC role emphasizes hands-on work with fine-tuning, MLOps pipelines, and end-to-end system awareness.

Qualifications

• Strong fundamentals in computer vision — segmentation, detection, classification, tracking.
• Experience with modern ML approaches including VLMs, LLMs, and foundation models.
• Experience designing robust evaluation metrics and ML eval harnesses.
• Product shipping experience with models in production, drift handling and latency budgeting.
• Ability to justify tooling decisions with data and explicit criteria.

Responsibilities

• Train and evaluate segmentation, classification, and mass-estimation models for the Mill Commercial camera pipeline.
• Optimize edge models for production performance and scale the ML pipeline end-to-end.
• Create and curate datasets per customer/vertical to meet accuracy targets across food types and environments.
• Analyze failure cases and drive data/modeled decisions to close accuracy gaps.
• Build annotation tooling and ground-truth generation workflows, including foundation-model-assisted labeling.
• Collaborate with MLOps and edge engineers on training practices, versioning, and deployment tradeoffs.

Skills

Computer vision

Segmentation

Detection

Classification

Tracking

Python

PyTorch

OpenCV

VLMs

LLMs

Foundation models

Agentic systems

Tools

Python

PyTorch

OpenCV

LLM frameworks

Weights & Biases

Job description

Mill is seeking a Computer Vision Engineer to advance the CV technology behind Mill Commercial, turning food waste streams into actionable intelligence for large kitchen operators.

You will own modeling, training infra, and cloud-side evaluation harnesses, while guiding data-groundtruth workflows and model deployment decisions. This IC role emphasizes hands-on work with fine-tuning, MLOps pipelines, and end-to-end system awareness.